Check pCVP2-BRI1-mCitrine specificity in scRNA-seq

Here we perform analysis against the custom reference. The results are exported and inlcuded in the SI table.

library(tidyverse)
library(Seurat)
library(cowplot)
library(ComplexHeatmap)
library(circlize)
library(GeneOverlap)
library(gprofiler2)
library(ggrepel)
library(ggplot2)
library(muscat)
library(purrr)
library(limma)
library(scran)

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ComplexHeatmap version 2.14.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================


========================================
circlize version 0.4.15
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================


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Welcome to Bioconductor

    Vignettes contain introductory material; view with
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Loading required package: scuttle

library(future)
#for 200gb ram 
options(future.globals.maxSize = 200000 * 1024^2)

sessionInfo()

R version 4.2.2 (2022-10-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: AlmaLinux 9.3 (Shamrock Pampas Cat)

Matrix products: default
BLAS/LAPACK: /hpc/group/pbenfeylab/tmn23/miniconda3/envs/muscat/lib/libopenblasp-r0.3.21.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
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[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats4    grid      stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] future_1.31.0               scran_1.26.0               
 [3] scuttle_1.8.0               SingleCellExperiment_1.20.0
 [5] SummarizedExperiment_1.28.0 Biobase_2.58.0             
 [7] GenomicRanges_1.50.0        GenomeInfoDb_1.34.8        
 [9] IRanges_2.32.0              S4Vectors_0.36.0           
[11] BiocGenerics_0.44.0         MatrixGenerics_1.10.0      
[13] matrixStats_0.63.0          limma_3.54.0               
[15] muscat_1.12.0               ggrepel_0.9.3              
[17] gprofiler2_0.2.1            GeneOverlap_1.34.0         
[19] circlize_0.4.15             ComplexHeatmap_2.14.0      
[21] cowplot_1.1.1               SeuratObject_4.1.3         
[23] Seurat_4.3.0                lubridate_1.9.2            
[25] forcats_1.0.0               stringr_1.5.0              
[27] dplyr_1.1.0                 purrr_1.0.1                
[29] readr_2.1.4                 tidyr_1.3.0                
[31] tibble_3.1.8                ggplot2_3.4.1              
[33] tidyverse_2.0.0            

loaded via a namespace (and not attached):
  [1] pbdZMQ_0.3-9              scattermore_0.8          
  [3] bit64_4.0.5               irlba_2.3.5.1            
  [5] DelayedArray_0.24.0       data.table_1.14.8        
  [7] KEGGREST_1.38.0           RCurl_1.98-1.10          
  [9] doParallel_1.0.17         generics_0.1.3           
 [11] ScaledMatrix_1.6.0        RhpcBLASctl_0.23-42      
 [13] RSQLite_2.2.20            RANN_2.6.1               
 [15] bit_4.0.5                 tzdb_0.3.0               
 [17] spatstat.data_3.0-0       httpuv_1.6.9             
 [19] viridis_0.6.2             hms_1.1.2                
 [21] evaluate_0.20             promises_1.2.0.1         
 [23] fansi_1.0.4               progress_1.2.2           
 [25] caTools_1.18.2            igraph_1.3.5             
 [27] DBI_1.1.3                 geneplotter_1.76.0       
 [29] htmlwidgets_1.6.1         spatstat.geom_3.0-6      
 [31] ellipsis_0.3.2            backports_1.4.1          
 [33] annotate_1.76.0           aod_1.3.2                
 [35] deldir_1.0-6              sparseMatrixStats_1.10.0 
 [37] vctrs_0.5.2               ROCR_1.0-11              
 [39] abind_1.4-5               cachem_1.0.6             
 [41] withr_2.5.0               progressr_0.13.0         
 [43] sctransform_0.3.5         prettyunits_1.1.1        
 [45] goftest_1.2-3             cluster_2.1.4            
 [47] IRdisplay_1.1             lazyeval_0.2.2           
 [49] crayon_1.5.2              genefilter_1.80.0        
 [51] spatstat.explore_3.0-6    edgeR_3.40.0             
 [53] pkgconfig_2.0.3           nlme_3.1-162             
 [55] vipor_0.4.5               blme_1.0-5               
 [57] rlang_1.0.6               globals_0.16.2           
 [59] lifecycle_1.0.3           miniUI_0.1.1.1           
 [61] rsvd_1.0.5                polyclip_1.10-4          
 [63] lmtest_0.9-40             Matrix_1.5-3             
 [65] IRkernel_1.3.2            boot_1.3-28.1            
 [67] zoo_1.8-11                base64enc_0.1-3          
 [69] beeswarm_0.4.0            ggridges_0.5.4           
 [71] GlobalOptions_0.1.2       png_0.1-8                
 [73] viridisLite_0.4.1         rjson_0.2.21             
 [75] bitops_1.0-7              KernSmooth_2.23-20       
 [77] Biostrings_2.66.0         blob_1.2.3               
 [79] DelayedMatrixStats_1.20.0 shape_1.4.6              
 [81] parallelly_1.34.0         spatstat.random_3.1-3    
 [83] beachmat_2.14.0           scales_1.2.1             
 [85] memoise_2.0.1             magrittr_2.0.3           
 [87] plyr_1.8.8                ica_1.0-3                
 [89] gplots_3.1.3              zlibbioc_1.44.0          
 [91] compiler_4.2.2            dqrng_0.3.0              
 [93] RColorBrewer_1.1-3        clue_0.3-64              
 [95] lme4_1.1-31               DESeq2_1.38.0            
 [97] fitdistrplus_1.1-8        cli_3.6.0                
 [99] XVector_0.38.0            lmerTest_3.1-3           
[101] listenv_0.9.0             patchwork_1.1.2          
[103] pbapply_1.7-0             TMB_1.9.2                
[105] MASS_7.3-58.2             tidyselect_1.2.0         
[107] stringi_1.7.12            BiocSingular_1.14.0      
[109] locfit_1.5-9.7            tools_4.2.2              
[111] timechange_0.2.0          future.apply_1.10.0      
[113] parallel_4.2.2            uuid_1.1-0               
[115] bluster_1.8.0             foreach_1.5.2            
[117] metapod_1.6.0             gridExtra_2.3            
[119] Rtsne_0.16                digest_0.6.31            
[121] shiny_1.7.4               Rcpp_1.0.10              
[123] broom_1.0.3               later_1.3.0              
[125] RcppAnnoy_0.0.20          httr_1.4.4               
[127] AnnotationDbi_1.60.0      Rdpack_2.4               
[129] colorspace_2.1-0          XML_3.99-0.13            
[131] tensor_1.5                reticulate_1.28          
[133] splines_4.2.2             statmod_1.5.0            
[135] uwot_0.1.14               spatstat.utils_3.0-1     
[137] scater_1.26.0             sp_1.6-0                 
[139] plotly_4.10.1             xtable_1.8-4             
[141] jsonlite_1.8.4            nloptr_2.0.3             
[143] R6_2.5.1                  pillar_1.8.1             
[145] htmltools_0.5.4           mime_0.12                
[147] glue_1.6.2                fastmap_1.1.0            
[149] minqa_1.2.5               BiocParallel_1.32.5      
[151] BiocNeighbors_1.16.0      codetools_0.2-19         
[153] utf8_1.2.3                lattice_0.20-45          
[155] spatstat.sparse_3.0-0     numDeriv_2016.8-1.1      
[157] pbkrtest_0.5.2            ggbeeswarm_0.7.1         
[159] leiden_0.4.3              gtools_3.9.4             
[161] survival_3.5-3            glmmTMB_1.1.5            
[163] repr_1.1.6                munsell_0.5.0            
[165] GetoptLong_1.0.5          GenomeInfoDbData_1.2.9   
[167] iterators_1.0.14          variancePartition_1.28.0 
[169] reshape2_1.4.4            gtable_0.3.1             
[171] rbibutils_2.2.13         

rc.integrated <- readRDS("../../CheWei/scRNA-seq/Integrated_Objects/rc.integrated_8S_CVP_BRI1_seu3_annotated_20230316.rds")

rc.integrated

An object of class Seurat 
71788 features across 55427 samples within 3 assays 
Active assay: SCT (25288 features, 0 variable features)
 2 other assays present: RNA, integrated
 4 dimensional reductions calculated: pca, umap, umap_3D, umap_2D

rc.integrated <- subset(rc.integrated, 
                        subset = orig.ident %in% c("sc_130",
                                              "sc_131",
                                              "sc_132",
                                              "sc_134",
                                              "sc_135",
                                              "sc_136"))

table(rc.integrated$orig.ident, rc.integrated$geno)

        
           WT bri1_T pCVP2_BRI1_Citrine_bri1_T
  sc_130 6589      0                         0
  sc_131    0   7615                         0
  sc_132    0      0                      6550
  sc_134 7745      0                         0
  sc_135    0   5038                         0
  sc_136    0      0                      6089

feature_names <- read_tsv("../data/features.tsv.gz", col_names = c("AGI", "Name", "Type")) %>%
  select(-Type) %>%
  distinct()

Rows: 32833 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (3): AGI, Name, Type

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

rc.integrated$geno <- factor(rc.integrated$geno, levels=c("WT", "bri1_T", "pCVP2_BRI1_Citrine_bri1_T"))

Cell and developmental stage metadata

• Developmental stage: time_zone
• Cell type:cell_type
• Combination of cell type and developmental stage: time_zone_cell_type

order <- c("Quiescent Center", "Ground Tissue","Columella", "Lateral Root Cap", "Atrichoblast", "Trichoblast", "Cortex", "Endodermis", "Phloem","Protophloem", "Xylem", "Procambium","Pericycle","Phloem Pole Pericycle", "Protoxylem", "Metaxylem", "Unknown")
palette <- c("#9400D3", "#DCD0FF","#5AB953", "#BFEF45", "#008080", "#21B6A8", "#82B6FF", "#0000FF","#E6194B", "#DD77EC", "#9A6324", "#FFE119", "#FF9900", "#FFD4E3", "#9A6324", "#DDAA6F", "#EEEEEE")
rc.integrated$cell_type <- factor(rc.integrated$cell_type, levels = order[sort(match(unique(rc.integrated$cell_type),order))])
color <- palette[sort(match(unique(rc.integrated$cell_type),order))]

options(repr.plot.width=16.5, repr.plot.height=6)
(Celltype_umap <- DimPlot(rc.integrated, 
                      reduction = "umap", 
                      group.by = "cell_type", 
                      cols = color, split.by = 'geno', 
                      ncol=3, 
                      pt.size = 0.5))

ggsave("../output/CVP/Cell_type_umap_square_all_samples.pdf", width=16.5, height=6)

options(repr.plot.width = 18, repr.plot.height = 6)

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="BRI1-mCitrine", split.by = "geno", order=T, max.cutoff = "q90", pt.size = 0.5)

ggsave("../output/CVP/BRI1-mCitrine_expression_all_samples.pdf", width=18.3, height=6)

Warning message in FeaturePlot(rc.integrated, features = "BRI1-mCitrine", split.by = "geno", :
“All cells have the same value (0) of BRI1-mCitrine.”

# expression of CVP2
options(repr.plot.width = 18, repr.plot.height = 6)

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="AT1G05470", split.by = "geno", order=T, max.cutoff = "q90", pt.size = 0.5)

ggsave("../output/CVP/CVP2_AT1G05470_expression_all_samples.pdf", width=18.3, height=6)

options(repr.plot.width=30, repr.plot.height=7)

DimPlot(rc.integrated, reduction = "umap", group.by = "cell_type", cols = color, split.by = 'orig.ident', pt.size = 0.75, ncol=8)

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="BRI1-mCitrine", split.by = "orig.ident", order=T, max.cutoff = "q80", pt.size = 0.5)

Warning message in FeaturePlot(rc.integrated, features = "BRI1-mCitrine", split.by = "orig.ident", :
“All cells have the same value (0) of BRI1-mCitrine.”
Warning message in FeaturePlot(rc.integrated, features = "BRI1-mCitrine", split.by = "orig.ident", :
“All cells have the same value (0) of BRI1-mCitrine.”

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="AT1G05470", split.by = "orig.ident", order=T, max.cutoff = "q80", pt.size = 0.5)

table(rc.integrated$orig.ident, rc.integrated$cell_type)

        
         Columella Lateral Root Cap Atrichoblast Trichoblast Cortex Endodermis
  sc_130       895             1058         1445        1000    972        725
  sc_131       672             1800         1441         900    777        490
  sc_132       474             1597         1089         916    720        544
  sc_134       582             2101         1171        1041    906        573
  sc_135       294              991         1055         707    544        480
  sc_136       649             1240         1176         871    878        617
        
         Phloem Xylem Procambium Pericycle
  sc_130     52   172        127       143
  sc_131    130   273        320       812
  sc_132    138   230        288       554
  sc_134    123   267        348       633
  sc_135     88   191        260       428
  sc_136     78   147        186       247

table(rc.integrated$orig.ident, rc.integrated$time_zone)

        
         Distal Columella Distal Lateral Root Cap Elongation Maturation
  sc_130              834                     699       2433       1206
  sc_131              626                     566       1873       1430
  sc_132              442                     678       1950       1511
  sc_134              535                     971       2472       1673
  sc_135              268                     201       1110        930
  sc_136              610                     581       2009       1302
        
         Meristem Proximal Columella Proximal Lateral Root Cap
  sc_130      998                 60                       359
  sc_131     1887                 36                      1197
  sc_132     1023                 31                       915
  sc_134      921                 44                      1129
  sc_135     1730                 26                       773
  sc_136      891                 37                       659

Convert to sce

#  construct sce manually
my_metadata <- data.frame(sample_id = rc.integrated$orig.ident,
                              group_id = rc.integrated$geno,
                              cluster_id = rc.integrated$cell_type, 
                             date=rc.integrated$rep) # include experimental rep as co-variate

sce <- SingleCellExperiment(assays = list(counts = rc.integrated@assays$RNA@counts),
	                            colData = my_metadata)

(sce <- prepSCE(sce, 
        kid = "cluster_id", # subpopulation assignments
        gid = "group_id",   # group IDs (ctrl/stim)
        sid = "sample_id",    # sample IDs (ctrl/stim.1234)
        drop = FALSE))        # drop all other colData columns

class: SingleCellExperiment 
dim: 28980 39626 
metadata(1): experiment_info
assays(1): counts
rownames(28980): AT1G01010 AT1G01020 ... AT5G39430 AT5G54075
rowData names(0):
colnames(39626): AAACCCACAACAGCCC_6 AAACCCACAGAGTAAT_6 ...
  TTTGTTGCATCGATAC_11 TTTGTTGTCAAGAGGC_11
colData names(4): cluster_id sample_id group_id date
reducedDimNames(0):
mainExpName: NULL
altExpNames(0):

pre-filtering

# remove undetected genes
sce <- sce[rowSums(counts(sce) > 0) > 0, ]
dim(sce)

1. 26993
2. 39626

# create pseudobulk profiles
pb <- aggregateData(sce,
    assay = "counts", fun = "sum",
    by = c("cluster_id", "sample_id"))
# one sheet per subpopulation
assayNames(pb)

1. 'Columella'
2. 'Lateral Root Cap'
3. 'Atrichoblast'
4. 'Trichoblast'
5. 'Cortex'
6. 'Endodermis'
7. 'Phloem'
8. 'Xylem'
9. 'Procambium'
10. 'Pericycle'

# pseudobulks for 1st subpopulation
t(head(assay(pb)))

A matrix: 6 × 6 of type dbl

	AT1G01010	AT1G01020	AT1G03987	AT1G01030	AT1G01040	AT1G01050
sc_130	68	97	1	21	19	1846
sc_131	46	92	0	10	17	1092
sc_132	32	52	0	10	10	901
sc_134	46	73	0	18	14	1210
sc_135	14	57	0	11	10	623
sc_136	55	81	0	19	16	1440

# experiment info for contrasts, add dates from csv

ei <- metadata(sce)$experiment_info

ei

ei$rep <- c(1, 1, 1, 2, 2, 2)
ei
#sample_date <- select(bscs, sample_id=sample, date=rep)

#ei <- left_join(ei, sample_date)

#ei

A data.frame: 6 × 3

sample_id	group_id	n_cells
<fct>	<fct>	<dbl>
sc_130	WT	6589
sc_131	bri1_T	7615
sc_132	pCVP2_BRI1_Citrine_bri1_T	6550
sc_134	WT	7745
sc_135	bri1_T	5038
sc_136	pCVP2_BRI1_Citrine_bri1_T	6089

A data.frame: 6 × 4

sample_id	group_id	n_cells	rep
<fct>	<fct>	<dbl>	<dbl>
sc_130	WT	6589	1
sc_131	bri1_T	7615	1
sc_132	pCVP2_BRI1_Citrine_bri1_T	6550	1
sc_134	WT	7745	2
sc_135	bri1_T	5038	2
sc_136	pCVP2_BRI1_Citrine_bri1_T	6089	2

mm <- model.matrix(~ 0 + ei$group_id + ei$rep)
dimnames(mm) <- list(ei$sample_id, c(levels(ei$group_id), "rep"))

mm

A matrix: 6 × 4 of type dbl

	WT	bri1_T	pCVP2_BRI1_Citrine_bri1_T	rep
sc_130	1	0	0	1
sc_131	0	1	0	1
sc_132	0	0	1	1
sc_134	1	0	0	2
sc_135	0	1	0	2
sc_136	0	0	1	2

contrast <- makeContrasts("pCVP2_BRI1_Citrine_bri1_T-bri1_T", 
                            "pCVP2_BRI1_Citrine_bri1_T-WT", levels = mm)

contrast

A matrix: 4 × 2 of type dbl

	pCVP2_BRI1_Citrine_bri1_T-bri1_T	pCVP2_BRI1_Citrine_bri1_T-WT
WT	0	-1
bri1_T	-1	0
pCVP2_BRI1_Citrine_bri1_T	1	1
rep	0	0

res <- pbDS(pb, design = mm, 
            contrast = contrast, 
            method="edgeR", 
            min_cells=5, 
            filter = c("none"))

  |======================================================================| 100%

DEG results

# DEG results with gene freqs
(res_to_write_frq <- resDS(sce, res, bind = "row", cpm=TRUE, frq=T))

A data.frame: 465062 × 24

gene	cluster_id	sc_130.cpm	sc_134.cpm	sc_131.cpm	sc_135.cpm	sc_132.cpm	sc_136.cpm	sc_130.frq	sc_134.frq	⋯	WT.frq	bri1_T.frq	pCVP2_BRI1_Citrine_bri1_T.frq	logFC	logCPM	F	p_val	p_adj.loc	p_adj.glb	contrast
<chr>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>
AT1G01010	Columella	9.860	9.66	8.300	4.610	9.790	10.200	0.07260	0.06870	⋯	0.071100	0.06110	0.07480	0.606000	3.2200	4.05e+00	0.04420	0.3010	0.2410	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01010	Columella	9.860	9.66	8.300	4.610	9.790	10.200	0.07260	0.06870	⋯	0.071100	0.06110	0.07480	0.057900	3.2200	4.42e-02	0.83300	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01020	Columella	14.100	15.30	16.600	18.800	15.900	15.000	0.09610	0.10300	⋯	0.098800	0.13700	0.09880	-0.193000	4.0200	6.53e-01	0.41900	0.8640	0.7690	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01020	Columella	14.100	15.30	16.600	18.800	15.900	15.000	0.09610	0.10300	⋯	0.098800	0.13700	0.09880	0.068000	4.0200	8.37e-02	0.77200	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G03987	Columella	0.145	0.00	0.000	0.000	0.000	0.000	0.00112	0.00000	⋯	0.000677	0.00000	0.00000	0.394000	-1.1500	2.05e-09	1.00000	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G03987	Columella	0.145	0.00	0.000	0.000	0.000	0.000	0.00112	0.00000	⋯	0.000677	0.00000	0.00000	-1.760000	-1.1500	2.16e-01	0.64200	1.0000	0.9950	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01030	Columella	3.050	3.78	1.800	3.620	3.060	3.520	0.02230	0.02750	⋯	0.024400	0.01970	0.02320	0.331000	1.8100	4.76e-01	0.49000	0.8760	0.7970	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01030	Columella	3.050	3.78	1.800	3.620	3.060	3.520	0.02230	0.02750	⋯	0.024400	0.01970	0.02320	-0.076900	1.8100	3.08e-02	0.86100	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01040	Columella	2.760	2.94	3.070	3.290	3.060	2.970	0.02010	0.02410	⋯	0.021700	0.02590	0.01960	-0.078900	1.7700	2.77e-02	0.86800	1.0000	0.9800	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01040	Columella	2.760	2.94	3.070	3.290	3.060	2.970	0.02010	0.02410	⋯	0.021700	0.02590	0.01960	0.076100	1.7700	2.75e-02	0.86800	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01050	Columella	268.000	254.00	197.000	205.000	276.000	267.000	0.76800	0.72700	⋯	0.752000	0.73500	0.76800	0.433000	7.9400	9.27e+00	0.00233	0.0367	0.0362	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01050	Columella	268.000	254.00	197.000	205.000	276.000	267.000	0.76800	0.72700	⋯	0.752000	0.73500	0.76800	0.056500	7.9400	1.61e-01	0.68800	1.0000	0.9980	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01060	Columella	0.435	0.84	0.722	0.988	0.306	0.556	0.00335	0.00687	⋯	0.004740	0.00725	0.00356	-0.975000	0.0563	5.80e-01	0.44600	0.8640	0.7870	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01060	Columella	0.435	0.84	0.722	0.988	0.306	0.556	0.00335	0.00687	⋯	0.004740	0.00725	0.00356	-0.510000	0.0563	1.60e-01	0.68900	1.0000	0.9980	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01070	Columella	0.145	0.21	1.440	0.329	0.612	0.185	0.00112	0.00172	⋯	0.001350	0.00932	0.00178	-1.160000	-0.1510	6.59e-01	0.41700	0.8640	0.7680	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01070	Columella	0.145	0.21	1.440	0.329	0.612	0.185	0.00112	0.00172	⋯	0.001350	0.00932	0.00178	1.120000	-0.1510	4.07e-01	0.52400	1.0000	0.9810	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01080	Columella	0.435	0.42	0.722	0.658	0.306	0.371	0.00335	0.00344	⋯	0.003390	0.00621	0.00267	-0.960000	-0.1520	4.20e-01	0.51700	0.8820	0.8020	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01080	Columella	0.435	0.42	0.722	0.658	0.306	0.371	0.00335	0.00344	⋯	0.003390	0.00621	0.00267	-0.291000	-0.1520	3.71e-02	0.84700	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01090	Columella	38.000	39.10	41.700	41.500	38.300	38.800	0.24200	0.25900	⋯	0.249000	0.28900	0.25600	-0.111000	5.3200	3.70e-01	0.54300	0.8920	0.8080	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01090	Columella	38.000	39.10	41.700	41.500	38.300	38.800	0.24200	0.25900	⋯	0.249000	0.28900	0.25600	-0.000277	5.3200	2.37e-06	0.99900	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01100	Columella	267.000	297.00	407.000	492.000	325.000	343.000	0.74600	0.76500	⋯	0.754000	0.89500	0.81700	-0.423000	8.4700	9.84e+00	0.00171	0.0290	0.0293	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01100	Columella	267.000	297.00	407.000	492.000	325.000	343.000	0.74600	0.76500	⋯	0.754000	0.89500	0.81700	0.246000	8.4700	3.33e+00	0.06820	1.0000	0.8040	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01110	Columella	2.180	2.52	2.160	0.658	3.060	1.670	0.01680	0.01890	⋯	0.017600	0.01350	0.01600	0.623000	1.3100	1.05e+00	0.30500	0.7890	0.6810	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01110	Columella	2.180	2.52	2.160	0.658	3.060	1.670	0.01680	0.01890	⋯	0.017600	0.01350	0.01600	-0.015900	1.3100	8.72e-04	0.97600	1.0000	1.0000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01120	Columella	2.030	3.15	1.980	0.658	3.670	2.970	0.01450	0.02410	⋯	0.018300	0.01240	0.01870	1.170000	1.5100	4.42e+00	0.03560	0.2620	0.2120	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01120	Columella	2.030	3.15	1.980	0.658	3.670	2.970	0.01450	0.02410	⋯	0.018300	0.01240	0.01870	0.373000	1.5100	5.95e-01	0.44000	1.0000	0.9810	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01130	Columella	0.435	1.26	1.080	0.658	1.840	0.927	0.00335	0.01030	⋯	0.006090	0.00828	0.00980	0.508000	0.4770	3.13e-01	0.57600	0.8920	0.8250	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01130	Columella	0.435	1.26	1.080	0.658	1.840	0.927	0.00335	0.01030	⋯	0.006090	0.00828	0.00980	0.702000	0.4770	6.49e-01	0.42000	1.0000	0.9810	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G01140	Columella	24.200	16.20	14.100	9.220	12.900	18.900	0.16000	0.11700	⋯	0.143000	0.10000	0.12000	0.482000	4.0700	3.76e+00	0.05240	0.3320	0.2670	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G01140	Columella	24.200	16.20	14.100	9.220	12.900	18.900	0.16000	0.11700	⋯	0.143000	0.10000	0.12000	-0.290000	4.0700	1.62e+00	0.20200	1.0000	0.9810	pCVP2_BRI1_Citrine_bri1_T-WT
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋱	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
AT1G49205	Pericycle	0	0.2940	0	0.0000	0	0.5790	0	0.00790	⋯	0.00644	0.000000	0.00749	4.6900	-1.72	4.54e+00	0.0748	0.497	0.329	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G49205	Pericycle	0	0.2940	0	0.0000	0	0.5790	0	0.00790	⋯	0.00644	0.000000	0.00749	0.8970	-1.72	4.59e-01	0.5220	0.901	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT2G07975	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	0.0461	-2.55	3.22e-11	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT2G07975	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	-2.1600	-2.55	4.11e-01	0.5440	0.901	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT3G53070	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	0.0461	-2.55	3.22e-11	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT3G53070	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	-2.1600	-2.55	4.11e-01	0.5440	0.901	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT3G08325	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	0.0461	-2.55	3.22e-11	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT3G08325	Pericycle	0	0.0588	0	0.0000	0	0.0000	0	0.00158	⋯	0.00129	0.000000	0.00000	-2.1600	-2.55	4.11e-01	0.5440	0.901	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT5G17345	Pericycle	0	0.1180	0	0.0000	0	0.0000	0	0.00316	⋯	0.00258	0.000000	0.00000	0.0682	-2.45	3.54e-11	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT5G17345	Pericycle	0	0.1180	0	0.0000	0	0.0000	0	0.00316	⋯	0.00258	0.000000	0.00000	-2.8700	-2.45	8.24e-01	0.3970	0.852	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G43722	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G43722	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT1G60025	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT1G60025	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT3G04440	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT3G04440	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT3G25014	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT3G25014	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT4G03765	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT4G03765	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT4G10190	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	-2.0700	-2.55	5.18e-01	0.4970	0.811	0.799	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT4G10190	Pericycle	0	0.0000	0	0.0797	0	0.0000	0	0.00000	⋯	0.00000	0.000806	0.00000	0.6950	-2.55	2.79e-09	1.0000	1.000	1.000	pCVP2_BRI1_Citrine_bri1_T-WT
AT2G19010	Pericycle	0	0.0000	0	0.0000	0	0.0965	0	0.00000	⋯	0.00000	0.000000	0.00125	2.3500	-2.55	6.80e-01	0.4400	0.811	0.783	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT2G19010	Pericycle	0	0.0000	0	0.0000	0	0.0965	0	0.00000	⋯	0.00000	0.000000	0.00125	2.9800	-2.55	8.31e-01	0.3950	0.852	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT2G05645	Pericycle	0	0.0000	0	0.0000	0	0.1930	0	0.00000	⋯	0.00000	0.000000	0.00125	3.2100	-2.44	1.36e+00	0.2860	0.756	0.662	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT2G05645	Pericycle	0	0.0000	0	0.0000	0	0.1930	0	0.00000	⋯	0.00000	0.000000	0.00125	3.9500	-2.44	1.65e+00	0.2440	0.806	0.981	pCVP2_BRI1_Citrine_bri1_T-WT
AT3G20362	Pericycle	0	0.0000	0	0.0000	0	0.7720	0	0.00000	⋯	0.00000	0.000000	0.00999	5.0900	-1.91	5.34e+00	0.0579	0.455	0.284	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT3G20362	Pericycle	0	0.0000	0	0.0000	0	0.7720	0	0.00000	⋯	0.00000	0.000000	0.00999	5.9400	-1.91	6.41e+00	0.0424	0.592	0.707	pCVP2_BRI1_Citrine_bri1_T-WT
AT4G03040	Pericycle	0	0.0000	0	0.0000	0	0.0965	0	0.00000	⋯	0.00000	0.000000	0.00125	2.3500	-2.55	6.80e-01	0.4400	0.811	0.783	pCVP2_BRI1_Citrine_bri1_T-bri1_T
AT4G03040	Pericycle	0	0.0000	0	0.0000	0	0.0965	0	0.00000	⋯	0.00000	0.000000	0.00125	2.9800	-2.55	8.31e-01	0.3950	0.852	0.981	pCVP2_BRI1_Citrine_bri1_T-WT

## all genes as background

all_bg <- res_to_write_frq

all_bg %>% filter(gene=="BRI1-mCitrine") %>%
arrange(desc(sc_136.cpm))

A data.frame: 20 × 24

gene	cluster_id	sc_130.cpm	sc_134.cpm	sc_131.cpm	sc_135.cpm	sc_132.cpm	sc_136.cpm	sc_130.frq	sc_134.frq	⋯	WT.frq	bri1_T.frq	pCVP2_BRI1_Citrine_bri1_T.frq	logFC	logCPM	F	p_val	p_adj.loc	p_adj.glb	contrast
<chr>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>
BRI1-mCitrine	Atrichoblast	0	0	0.1760	0.0766	5.090	8.22	0	0	⋯	0	0.00280	0.0870	5.60	1.1000	133.00	1.68e-07	2.16e-05	5.72e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Atrichoblast	0	0	0.1760	0.0766	5.090	8.22	0	0	⋯	0	0.00280	0.0870	10.20	1.1000	160.00	6.42e-08	7.86e-04	1.30e-04	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Columella	0	0	0.3610	0.3290	5.810	7.60	0	0	⋯	0	0.00311	0.0490	4.12	1.4000	37.30	1.01e-09	1.34e-07	1.02e-06	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Columella	0	0	0.3610	0.3290	5.810	7.60	0	0	⋯	0	0.00311	0.0490	7.99	1.4000	66.20	4.22e-16	1.09e-12	8.64e-12	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Lateral Root Cap	0	0	0.0515	0.1630	3.080	3.94	0	0	⋯	0	0.00107	0.0271	5.03	0.3110	60.80	4.33e-05	3.70e-03	2.26e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Lateral Root Cap	0	0	0.0515	0.1630	3.080	3.94	0	0	⋯	0	0.00107	0.0271	8.67	0.3110	72.80	2.22e-05	1.37e-01	1.29e-02	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Trichoblast	0	0	0.4060	0.3200	3.200	2.59	0	0	⋯	0	0.00871	0.0862	2.98	0.2080	50.70	2.01e-05	2.52e-03	1.29e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Trichoblast	0	0	0.4060	0.3200	3.200	2.59	0	0	⋯	0	0.00871	0.0862	9.36	0.2080	157.00	7.98e-08	6.49e-04	1.56e-04	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Phloem	0	0	0.0000	0.0000	0.000	2.56	0	0	⋯	0	0.00000	0.0139	4.12	0.6840	1.54	2.15e-01	9.13e-01	5.81e-01	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Phloem	0	0	0.0000	0.0000	0.000	2.56	0	0	⋯	0	0.00000	0.0139	4.61	0.6840	1.88	1.71e-01	1.00e+00	9.61e-01	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Xylem	0	0	0.3750	0.2570	0.794	2.18	0	0	⋯	0	0.00647	0.0345	1.99	-0.0746	2.98	1.03e-01	4.84e-01	3.95e-01	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Xylem	0	0	0.3750	0.2570	0.794	2.18	0	0	⋯	0	0.00647	0.0345	5.95	-0.0746	11.40	3.87e-03	2.38e-01	2.71e-01	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Procambium	0	0	0.0000	0.0000	2.790	2.12	0	0	⋯	0	0.00000	0.0443	6.67	0.3190	19.70	1.92e-04	1.05e-02	6.44e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Procambium	0	0	0.0000	0.0000	2.790	2.12	0	0	⋯	0	0.00000	0.0443	6.57	0.3190	16.00	5.76e-04	8.88e-02	9.90e-02	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Pericycle	0	0	0.4970	0.4780	2.660	2.03	0	0	⋯	0	0.01130	0.0724	2.25	0.2310	19.50	2.78e-03	1.41e-01	4.09e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Pericycle	0	0	0.4970	0.4780	2.660	2.03	0	0	⋯	0	0.01130	0.0724	7.82	0.2310	48.40	1.76e-04	2.48e-01	5.04e-02	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Cortex	0	0	0.2090	0.1940	1.420	1.68	0	0	⋯	0	0.00454	0.0300	2.89	-0.4290	18.50	2.56e-03	5.77e-02	3.87e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Cortex	0	0	0.2090	0.1940	1.420	1.68	0	0	⋯	0	0.00454	0.0300	7.55	-0.4290	41.30	1.98e-04	1.99e-01	5.42e-02	pCVP2_BRI1_Citrine_bri1_T-WT
BRI1-mCitrine	Endodermis	0	0	0.3760	0.3890	0.508	1.36	0	0	⋯	0	0.00825	0.0233	1.22	-0.7470	2.41	1.60e-01	5.36e-01	5.00e-01	pCVP2_BRI1_Citrine_bri1_T-bri1_T
BRI1-mCitrine	Endodermis	0	0	0.3760	0.3890	0.508	1.36	0	0	⋯	0	0.00825	0.0233	6.60	-0.7470	22.00	1.62e-03	4.73e-01	1.78e-01	pCVP2_BRI1_Citrine_bri1_T-WT

length(unique(all_bg$gene))

26993

#total DE genes p_adj.loc < 0.05, abs(logFC) > 1.5
sig_DE <- filter(res_to_write_frq, p_adj.loc<=0.05 & abs(logFC) > log2(1.5))
sig_DE <- left_join(sig_DE, feature_names, by=c("gene"="AGI"))

length(unique(sig_DE$gene))

10281

# filter gene freqs to avoid calling lowly detected genes
sig_DE_fil <- filter(sig_DE, WT.frq >=0.05 | bri1_T.frq >=0.05 | pCVP2_BRI1_Citrine_bri1_T.frq >=0.05)

length(unique(sig_DE_fil$gene))

8694

# load TFs
TF_list <- read_csv("../data/Kay_TF_thalemine_annotations.csv", col_names = c("gene", "TF_Name", "Description"))

Rows: 2485 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): gene, TF_Name, Description

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

sig_DE_fil <- left_join(sig_DE_fil, TF_list)

Joining with `by = join_by(gene)`

# label up vs down
sig_DE_fil <- sig_DE_fil %>%
  mutate(up_dn_label = case_when(logFC >=log2(1.5) ~ "Up",  
                                       logFC <=log2(1/1.5) ~ "Down",
                                       TRUE ~ "Not DE"))

sig_DE_fil$clust_up_dn <- paste(sig_DE_fil$cluster_id, sig_DE_fil$up_dn_label, sep="_")

sig_DE_fil

A data.frame: 15309 × 29

gene	cluster_id	sc_130.cpm	sc_134.cpm	sc_131.cpm	sc_135.cpm	sc_132.cpm	sc_136.cpm	sc_130.frq	sc_134.frq	⋯	F	p_val	p_adj.loc	p_adj.glb	contrast	Name	TF_Name	Description	up_dn_label	clust_up_dn
<chr>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<chr>	<chr>	<chr>	<chr>	<chr>
AT1G01240	Columella	31.90	25.20	15.30	14.20	23.00	30.00	0.2090	0.1800	⋯	15.40	8.59e-05	2.69e-03	3.66e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01240	NA	NA	Up	Columella_Up
AT1G01580	Columella	41.20	32.80	15.20	18.10	35.50	32.60	0.2500	0.2160	⋯	26.50	2.70e-07	2.02e-05	7.79e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	FRO2	NA	NA	Up	Columella_Up
AT1G01620	Columella	623.00	348.00	256.00	189.00	287.00	386.00	0.9340	0.8040	⋯	21.40	3.71e-06	1.97e-04	4.11e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	PIP1-3	NA	NA	Up	Columella_Up
AT1G01640	Columella	10.70	10.50	3.07	6.58	12.20	7.97	0.0626	0.0687	⋯	12.30	4.50e-04	1.02e-02	1.17e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01640	AT1G01640	BTB/POZ domain-containing protein	Up	Columella_Up
AT1G01725	Columella	14.90	16.20	4.87	4.28	16.20	18.70	0.1030	0.1190	⋯	43.00	5.57e-11	9.57e-09	7.61e-08	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01725	NA	NA	Up	Columella_Up
AT1G02430	Columella	8.99	7.98	5.23	3.29	6.73	11.70	0.0648	0.0619	⋯	10.70	1.10e-03	2.06e-02	2.17e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ATARFD1B	NA	NA	Up	Columella_Up
AT1G02610	Columella	23.10	23.30	13.50	10.90	23.60	22.60	0.1450	0.1580	⋯	15.30	9.08e-05	2.81e-03	3.80e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G02610	NA	NA	Up	Columella_Up
AT1G02860	Columella	70.90	71.80	51.40	38.50	77.40	70.30	0.3270	0.3280	⋯	16.50	4.82e-05	1.66e-03	2.43e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	BAH1	NA	NA	Up	Columella_Up
AT1G02870	Columella	6.24	17.00	18.60	22.70	11.90	11.70	0.0425	0.0945	⋯	11.60	6.48e-04	1.36e-02	1.51e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G02870	NA	NA	Down	Columella_Down
AT1G03030	Columella	19.70	19.70	13.20	14.80	19.90	24.90	0.1400	0.1370	⋯	8.76	3.07e-03	4.53e-02	4.38e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03030	NA	NA	Up	Columella_Up
AT1G03200	Columella	14.20	13.40	4.69	6.91	12.90	13.50	0.0883	0.1030	⋯	17.30	3.15e-05	1.17e-03	1.79e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03200	NA	NA	Up	Columella_Up
AT1G03850	Columella	58.40	53.40	42.00	38.50	62.10	88.80	0.2980	0.2770	⋯	25.60	4.23e-07	2.97e-05	1.05e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03850	NA	NA	Up	Columella_Up
AT1G03870	Columella	221.00	105.00	95.20	53.00	117.00	139.00	0.6830	0.4900	⋯	29.50	5.65e-08	4.88e-06	2.58e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	FLA9	NA	NA	Up	Columella_Up
AT1G04100	Columella	22.20	24.40	36.10	35.60	24.50	21.10	0.1490	0.1600	⋯	11.00	9.21e-04	1.80e-02	1.93e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	IAA10	IAA10	indoleacetic acid-induced protein 10	Down	Columella_Down
AT1G04180	Columella	20.30	20.20	6.13	9.22	11.00	10.00	0.0782	0.0893	⋯	15.10	1.03e-04	1.43e-02	3.56e-02	pCVP2_BRI1_Citrine_bri1_T-WT	YUC9	NA	NA	Down	Columella_Down
AT1G04280	Columella	14.10	13.40	5.23	4.61	14.40	13.40	0.0883	0.1010	⋯	24.70	6.79e-07	4.48e-05	1.45e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G04280	NA	NA	Up	Columella_Up
AT1G04870	Columella	2.18	2.94	8.30	12.20	3.37	4.08	0.0168	0.0223	⋯	16.70	4.28e-05	1.51e-03	2.24e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	PRMT10	NA	NA	Down	Columella_Down
AT1G05680	Columella	1080.00	1030.00	730.00	738.00	1180.00	1110.00	0.7550	0.6740	⋯	29.30	6.39e-08	5.49e-06	2.82e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	UGT74E2	NA	NA	Up	Columella_Up
AT1G05840	Columella	7.54	9.24	3.25	5.93	10.40	7.23	0.0547	0.0739	⋯	8.60	3.36e-03	4.86e-02	4.65e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G05840	NA	NA	Up	Columella_Up
AT1G06090	Columella	81.10	124.00	88.70	37.50	144.00	79.90	0.2020	0.2290	⋯	24.50	7.40e-07	4.81e-05	1.52e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G06090	NA	NA	Up	Columella_Up
AT1G06330	Columella	54.40	46.40	20.20	21.10	34.30	41.70	0.2800	0.2440	⋯	20.80	5.25e-06	2.64e-04	5.20e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G06330	NA	NA	Up	Columella_Up
AT1G07030	Columella	71.80	58.00	44.70	43.80	65.80	66.80	0.4010	0.3570	⋯	11.20	8.39e-04	1.67e-02	1.81e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07030	NA	NA	Up	Columella_Up
AT1G07070	Columella	5.22	9.03	17.00	21.70	10.70	11.70	0.0402	0.0704	⋯	9.73	1.81e-03	3.02e-02	3.06e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RPL35AA	NA	NA	Down	Columella_Down
AT1G07160	Columella	209.00	149.00	113.00	116.00	179.00	253.00	0.5520	0.4600	⋯	36.70	1.38e-09	1.76e-07	1.31e-06	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07160	NA	NA	Up	Columella_Up
AT1G07175	Columella	158.00	134.00	81.30	100.00	141.00	162.00	0.4590	0.4020	⋯	22.40	2.21e-06	1.25e-04	2.95e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07175	NA	NA	Up	Columella_Up
AT1G07290	Columella	36.40	29.40	11.70	16.80	20.80	35.20	0.1790	0.1620	⋯	21.50	3.56e-06	1.91e-04	4.00e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	GONST2	NA	NA	Up	Columella_Up
AT1G07930	Columella	39.60	49.60	69.30	81.60	49.30	47.80	0.2640	0.2660	⋯	13.20	2.84e-04	7.14e-03	8.47e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	A1	NA	NA	Down	Columella_Down
AT1G08310	Columella	7.25	11.10	9.20	2.96	16.80	8.53	0.0525	0.0704	⋯	10.50	1.17e-03	2.16e-02	2.26e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G08310	NA	NA	Up	Columella_Up
AT1G08500	Columella	35.70	19.10	11.90	9.22	14.10	19.80	0.2110	0.1480	⋯	9.23	2.38e-03	3.72e-02	3.67e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ENODL18	NA	NA	Up	Columella_Up
AT1G08890	Columella	11.70	13.90	5.05	2.63	8.57	13.50	0.0827	0.1050	⋯	19.90	8.27e-06	3.88e-04	7.02e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	SUGTL4	NA	NA	Up	Columella_Up
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋱	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
AT2G17660	Pericycle	0.982	1.4700	17.000	15.700	4.6400	2.700	0.02800	0.03160	⋯	55.1	5.99e-05	0.0317	0.002840	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G17660	NA	NA	Down	Pericycle_Down
AT2G18620	Pericycle	1.720	1.9400	11.100	11.600	2.9100	3.470	0.04900	0.04580	⋯	53.9	6.52e-05	0.0327	0.003030	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G18620	NA	NA	Down	Pericycle_Down
AT2G26910	Pericycle	3.680	2.3500	10.900	8.450	1.9800	1.450	0.08390	0.06160	⋯	80.5	1.45e-05	0.0166	0.001030	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ABCG32	NA	NA	Down	Pericycle_Down
AT2G33790	Pericycle	12.800	11.3000	59.400	38.700	20.2000	7.720	0.28000	0.19600	⋯	43.1	1.46e-04	0.0411	0.005280	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AGP30	NA	NA	Down	Pericycle_Down
AT2G33860	Pericycle	2.210	1.7000	5.710	7.330	0.8650	1.740	0.06290	0.04420	⋯	41.2	1.71e-04	0.0435	0.005930	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ARF3	ETT	Transcriptional factor B3 family protein / auxin-responsive factor AUX/IAA-like protein	Down	Pericycle_Down
AT2G36640	Pericycle	0.000	0.8820	6.640	10.400	1.1100	1.250	0.00000	0.01260	⋯	41.9	1.61e-04	0.0432	0.005700	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ECP63	NA	NA	Down	Pericycle_Down
AT2G37540	Pericycle	28.500	20.9000	3.540	2.710	11.6000	18.500	0.28000	0.25400	⋯	47.8	1.00e-04	0.0386	0.004090	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G37540	NA	NA	Up	Pericycle_Up
AT2G37870	Pericycle	0.982	5.5800	66.300	68.100	7.1700	5.880	0.02100	0.04270	⋯	60.2	4.32e-05	0.0294	0.002260	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G37870	NA	NA	Down	Pericycle_Down
AT2G38530	Pericycle	133.000	198.0000	110.000	84.100	326.0000	280.000	0.19600	0.22700	⋯	39.7	1.95e-04	0.0458	0.006530	pCVP2_BRI1_Citrine_bri1_T-bri1_T	LTP2	NA	NA	Up	Pericycle_Up
AT2G39681	Pericycle	10.300	8.8800	4.720	3.750	14.3000	13.800	0.18900	0.14100	⋯	57.3	5.19e-05	0.0297	0.002550	pCVP2_BRI1_Citrine_bri1_T-bri1_T	TAS2	NA	NA	Up	Pericycle_Up
AT2G39700	Pericycle	12.500	10.2000	8.690	4.940	35.5000	19.600	0.04900	0.05530	⋯	74.4	1.95e-05	0.0181	0.001270	pCVP2_BRI1_Citrine_bri1_T-bri1_T	EXPA4	NA	NA	Up	Pericycle_Up
AT2G45050	Pericycle	3.930	2.8200	27.900	17.100	5.3800	4.150	0.09790	0.05850	⋯	95.0	7.65e-06	0.0142	0.000667	pCVP2_BRI1_Citrine_bri1_T-bri1_T	GATA2	GATA2	GATA transcription factor 2	Down	Pericycle_Down
AT2G46400	Pericycle	28.200	50.7000	107.000	115.000	38.2000	37.100	0.16800	0.31300	⋯	37.6	2.36e-04	0.0497	0.007440	pCVP2_BRI1_Citrine_bri1_T-bri1_T	WRKY46	WRKY46	WRKY DNA-binding protein 46	Down	Pericycle_Down
AT2G48010	Pericycle	5.400	3.7000	8.260	7.570	2.4100	2.320	0.13300	0.08060	⋯	39.4	2.01e-04	0.0465	0.006650	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RKF3	NA	NA	Down	Pericycle_Down
AT4G01650	Pericycle	24.100	39.0000	11.400	9.640	41.6000	39.900	0.32200	0.39200	⋯	54.3	6.35e-05	0.0325	0.002970	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G01650	NA	NA	Up	Pericycle_Up
AT4G04223	Pericycle	1.720	0.1760	4.780	4.220	0.0000	0.000	0.02800	0.00474	⋯	51.7	1.43e-04	0.0409	0.005210	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G04223	NA	NA	Down	Pericycle_Down
AT4G11190	Pericycle	80.000	64.4000	197.000	204.000	91.7000	59.800	0.38500	0.27800	⋯	41.5	1.66e-04	0.0435	0.005820	pCVP2_BRI1_Citrine_bri1_T-bri1_T	DIR13	NA	NA	Down	Pericycle_Down
AT4G11211	Pericycle	250.000	269.0000	96.700	84.300	338.0000	314.000	0.82500	0.83900	⋯	87.8	1.04e-05	0.0156	0.000819	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G11211	NA	NA	Up	Pericycle_Up
AT4G12430	Pericycle	14.000	14.6000	5.090	4.620	12.3000	12.800	0.18200	0.18800	⋯	38.3	2.21e-04	0.0491	0.007120	pCVP2_BRI1_Citrine_bri1_T-bri1_T	TPPF	NA	NA	Up	Pericycle_Up
AT4G13860	Pericycle	8.100	10.6000	6.710	5.820	25.0000	18.600	0.15400	0.18500	⋯	50.9	8.01e-05	0.0357	0.003490	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G13860	NA	NA	Up	Pericycle_Up
AT4G15920	Pericycle	12.000	13.5000	2.730	1.200	12.4000	16.700	0.23800	0.23400	⋯	58.8	4.73e-05	0.0294	0.002400	pCVP2_BRI1_Citrine_bri1_T-bri1_T	SWEET17	NA	NA	Up	Pericycle_Up
AT4G16000	Pericycle	0.000	0.0588	3.910	3.670	0.0618	0.482	0.00000	0.00158	⋯	38.2	2.24e-04	0.0491	0.007180	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G16000	NA	NA	Down	Pericycle_Down
AT4G16990	Pericycle	12.000	5.8800	0.124	0.159	4.5100	3.090	0.22400	0.12500	⋯	95.0	7.67e-06	0.0142	0.000668	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RLM3	NA	NA	Up	Pericycle_Up
AT4G22214	Pericycle	16.400	12.2000	55.200	32.400	17.1000	14.100	0.31500	0.20100	⋯	45.5	1.20e-04	0.0386	0.004620	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G22214	NA	NA	Down	Pericycle_Down
AT4G23450	Pericycle	11.800	15.3000	4.970	4.940	16.4000	17.800	0.18200	0.22300	⋯	63.3	3.59e-05	0.0270	0.001980	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AIRP1	NA	NA	Up	Pericycle_Up
AT4G23680	Pericycle	0.245	0.7050	5.900	3.430	0.3090	0.386	0.00699	0.00632	⋯	50.3	8.35e-05	0.0365	0.003590	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G23680	NA	NA	Down	Pericycle_Down
AT4G30660	Pericycle	8.840	10.2000	69.500	52.900	16.8000	23.400	0.22400	0.20400	⋯	41.1	1.73e-04	0.0435	0.005980	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G30660	NA	NA	Down	Pericycle_Down
AT4G36880	Pericycle	24.100	23.6000	63.600	51.900	26.6000	23.000	0.32200	0.27600	⋯	37.5	2.39e-04	0.0500	0.007510	pCVP2_BRI1_Citrine_bri1_T-bri1_T	CP1	NA	NA	Down	Pericycle_Down
AT4G39940	Pericycle	0.736	1.3500	20.100	16.000	5.5600	2.890	0.02100	0.02530	⋯	46.9	1.07e-04	0.0386	0.004290	pCVP2_BRI1_Citrine_bri1_T-bri1_T	APK2	NA	NA	Down	Pericycle_Down
AT4G39950	Pericycle	2.700	2.5300	57.000	49.300	9.8300	5.110	0.02800	0.04900	⋯	124.0	2.71e-06	0.0102	0.000338	pCVP2_BRI1_Citrine_bri1_T-bri1_T	CYP79B2	NA	NA	Down	Pericycle_Down

sig_DE_fil
write.csv(sig_DE_fil, file = "../output/CVP/pCVP2_Citrine_celltype_EdgeR_q0.05_FC1.5_r_v_4_20240429.csv")

A data.frame: 15309 × 29

gene	cluster_id	sc_130.cpm	sc_134.cpm	sc_131.cpm	sc_135.cpm	sc_132.cpm	sc_136.cpm	sc_130.frq	sc_134.frq	⋯	F	p_val	p_adj.loc	p_adj.glb	contrast	Name	TF_Name	Description	up_dn_label	clust_up_dn
<chr>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<chr>	<chr>	<chr>	<chr>	<chr>
AT1G01240	Columella	31.90	25.20	15.30	14.20	23.00	30.00	0.2090	0.1800	⋯	15.40	8.59e-05	2.69e-03	3.66e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01240	NA	NA	Up	Columella_Up
AT1G01580	Columella	41.20	32.80	15.20	18.10	35.50	32.60	0.2500	0.2160	⋯	26.50	2.70e-07	2.02e-05	7.79e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	FRO2	NA	NA	Up	Columella_Up
AT1G01620	Columella	623.00	348.00	256.00	189.00	287.00	386.00	0.9340	0.8040	⋯	21.40	3.71e-06	1.97e-04	4.11e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	PIP1-3	NA	NA	Up	Columella_Up
AT1G01640	Columella	10.70	10.50	3.07	6.58	12.20	7.97	0.0626	0.0687	⋯	12.30	4.50e-04	1.02e-02	1.17e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01640	AT1G01640	BTB/POZ domain-containing protein	Up	Columella_Up
AT1G01725	Columella	14.90	16.20	4.87	4.28	16.20	18.70	0.1030	0.1190	⋯	43.00	5.57e-11	9.57e-09	7.61e-08	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G01725	NA	NA	Up	Columella_Up
AT1G02430	Columella	8.99	7.98	5.23	3.29	6.73	11.70	0.0648	0.0619	⋯	10.70	1.10e-03	2.06e-02	2.17e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ATARFD1B	NA	NA	Up	Columella_Up
AT1G02610	Columella	23.10	23.30	13.50	10.90	23.60	22.60	0.1450	0.1580	⋯	15.30	9.08e-05	2.81e-03	3.80e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G02610	NA	NA	Up	Columella_Up
AT1G02860	Columella	70.90	71.80	51.40	38.50	77.40	70.30	0.3270	0.3280	⋯	16.50	4.82e-05	1.66e-03	2.43e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	BAH1	NA	NA	Up	Columella_Up
AT1G02870	Columella	6.24	17.00	18.60	22.70	11.90	11.70	0.0425	0.0945	⋯	11.60	6.48e-04	1.36e-02	1.51e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G02870	NA	NA	Down	Columella_Down
AT1G03030	Columella	19.70	19.70	13.20	14.80	19.90	24.90	0.1400	0.1370	⋯	8.76	3.07e-03	4.53e-02	4.38e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03030	NA	NA	Up	Columella_Up
AT1G03200	Columella	14.20	13.40	4.69	6.91	12.90	13.50	0.0883	0.1030	⋯	17.30	3.15e-05	1.17e-03	1.79e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03200	NA	NA	Up	Columella_Up
AT1G03850	Columella	58.40	53.40	42.00	38.50	62.10	88.80	0.2980	0.2770	⋯	25.60	4.23e-07	2.97e-05	1.05e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G03850	NA	NA	Up	Columella_Up
AT1G03870	Columella	221.00	105.00	95.20	53.00	117.00	139.00	0.6830	0.4900	⋯	29.50	5.65e-08	4.88e-06	2.58e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	FLA9	NA	NA	Up	Columella_Up
AT1G04100	Columella	22.20	24.40	36.10	35.60	24.50	21.10	0.1490	0.1600	⋯	11.00	9.21e-04	1.80e-02	1.93e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	IAA10	IAA10	indoleacetic acid-induced protein 10	Down	Columella_Down
AT1G04180	Columella	20.30	20.20	6.13	9.22	11.00	10.00	0.0782	0.0893	⋯	15.10	1.03e-04	1.43e-02	3.56e-02	pCVP2_BRI1_Citrine_bri1_T-WT	YUC9	NA	NA	Down	Columella_Down
AT1G04280	Columella	14.10	13.40	5.23	4.61	14.40	13.40	0.0883	0.1010	⋯	24.70	6.79e-07	4.48e-05	1.45e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G04280	NA	NA	Up	Columella_Up
AT1G04870	Columella	2.18	2.94	8.30	12.20	3.37	4.08	0.0168	0.0223	⋯	16.70	4.28e-05	1.51e-03	2.24e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	PRMT10	NA	NA	Down	Columella_Down
AT1G05680	Columella	1080.00	1030.00	730.00	738.00	1180.00	1110.00	0.7550	0.6740	⋯	29.30	6.39e-08	5.49e-06	2.82e-05	pCVP2_BRI1_Citrine_bri1_T-bri1_T	UGT74E2	NA	NA	Up	Columella_Up
AT1G05840	Columella	7.54	9.24	3.25	5.93	10.40	7.23	0.0547	0.0739	⋯	8.60	3.36e-03	4.86e-02	4.65e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G05840	NA	NA	Up	Columella_Up
AT1G06090	Columella	81.10	124.00	88.70	37.50	144.00	79.90	0.2020	0.2290	⋯	24.50	7.40e-07	4.81e-05	1.52e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G06090	NA	NA	Up	Columella_Up
AT1G06330	Columella	54.40	46.40	20.20	21.10	34.30	41.70	0.2800	0.2440	⋯	20.80	5.25e-06	2.64e-04	5.20e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G06330	NA	NA	Up	Columella_Up
AT1G07030	Columella	71.80	58.00	44.70	43.80	65.80	66.80	0.4010	0.3570	⋯	11.20	8.39e-04	1.67e-02	1.81e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07030	NA	NA	Up	Columella_Up
AT1G07070	Columella	5.22	9.03	17.00	21.70	10.70	11.70	0.0402	0.0704	⋯	9.73	1.81e-03	3.02e-02	3.06e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RPL35AA	NA	NA	Down	Columella_Down
AT1G07160	Columella	209.00	149.00	113.00	116.00	179.00	253.00	0.5520	0.4600	⋯	36.70	1.38e-09	1.76e-07	1.31e-06	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07160	NA	NA	Up	Columella_Up
AT1G07175	Columella	158.00	134.00	81.30	100.00	141.00	162.00	0.4590	0.4020	⋯	22.40	2.21e-06	1.25e-04	2.95e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G07175	NA	NA	Up	Columella_Up
AT1G07290	Columella	36.40	29.40	11.70	16.80	20.80	35.20	0.1790	0.1620	⋯	21.50	3.56e-06	1.91e-04	4.00e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	GONST2	NA	NA	Up	Columella_Up
AT1G07930	Columella	39.60	49.60	69.30	81.60	49.30	47.80	0.2640	0.2660	⋯	13.20	2.84e-04	7.14e-03	8.47e-03	pCVP2_BRI1_Citrine_bri1_T-bri1_T	A1	NA	NA	Down	Columella_Down
AT1G08310	Columella	7.25	11.10	9.20	2.96	16.80	8.53	0.0525	0.0704	⋯	10.50	1.17e-03	2.16e-02	2.26e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT1G08310	NA	NA	Up	Columella_Up
AT1G08500	Columella	35.70	19.10	11.90	9.22	14.10	19.80	0.2110	0.1480	⋯	9.23	2.38e-03	3.72e-02	3.67e-02	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ENODL18	NA	NA	Up	Columella_Up
AT1G08890	Columella	11.70	13.90	5.05	2.63	8.57	13.50	0.0827	0.1050	⋯	19.90	8.27e-06	3.88e-04	7.02e-04	pCVP2_BRI1_Citrine_bri1_T-bri1_T	SUGTL4	NA	NA	Up	Columella_Up
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋱	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
AT2G17660	Pericycle	0.982	1.4700	17.000	15.700	4.6400	2.700	0.02800	0.03160	⋯	55.1	5.99e-05	0.0317	0.002840	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G17660	NA	NA	Down	Pericycle_Down
AT2G18620	Pericycle	1.720	1.9400	11.100	11.600	2.9100	3.470	0.04900	0.04580	⋯	53.9	6.52e-05	0.0327	0.003030	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G18620	NA	NA	Down	Pericycle_Down
AT2G26910	Pericycle	3.680	2.3500	10.900	8.450	1.9800	1.450	0.08390	0.06160	⋯	80.5	1.45e-05	0.0166	0.001030	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ABCG32	NA	NA	Down	Pericycle_Down
AT2G33790	Pericycle	12.800	11.3000	59.400	38.700	20.2000	7.720	0.28000	0.19600	⋯	43.1	1.46e-04	0.0411	0.005280	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AGP30	NA	NA	Down	Pericycle_Down
AT2G33860	Pericycle	2.210	1.7000	5.710	7.330	0.8650	1.740	0.06290	0.04420	⋯	41.2	1.71e-04	0.0435	0.005930	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ARF3	ETT	Transcriptional factor B3 family protein / auxin-responsive factor AUX/IAA-like protein	Down	Pericycle_Down
AT2G36640	Pericycle	0.000	0.8820	6.640	10.400	1.1100	1.250	0.00000	0.01260	⋯	41.9	1.61e-04	0.0432	0.005700	pCVP2_BRI1_Citrine_bri1_T-bri1_T	ECP63	NA	NA	Down	Pericycle_Down
AT2G37540	Pericycle	28.500	20.9000	3.540	2.710	11.6000	18.500	0.28000	0.25400	⋯	47.8	1.00e-04	0.0386	0.004090	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G37540	NA	NA	Up	Pericycle_Up
AT2G37870	Pericycle	0.982	5.5800	66.300	68.100	7.1700	5.880	0.02100	0.04270	⋯	60.2	4.32e-05	0.0294	0.002260	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT2G37870	NA	NA	Down	Pericycle_Down
AT2G38530	Pericycle	133.000	198.0000	110.000	84.100	326.0000	280.000	0.19600	0.22700	⋯	39.7	1.95e-04	0.0458	0.006530	pCVP2_BRI1_Citrine_bri1_T-bri1_T	LTP2	NA	NA	Up	Pericycle_Up
AT2G39681	Pericycle	10.300	8.8800	4.720	3.750	14.3000	13.800	0.18900	0.14100	⋯	57.3	5.19e-05	0.0297	0.002550	pCVP2_BRI1_Citrine_bri1_T-bri1_T	TAS2	NA	NA	Up	Pericycle_Up
AT2G39700	Pericycle	12.500	10.2000	8.690	4.940	35.5000	19.600	0.04900	0.05530	⋯	74.4	1.95e-05	0.0181	0.001270	pCVP2_BRI1_Citrine_bri1_T-bri1_T	EXPA4	NA	NA	Up	Pericycle_Up
AT2G45050	Pericycle	3.930	2.8200	27.900	17.100	5.3800	4.150	0.09790	0.05850	⋯	95.0	7.65e-06	0.0142	0.000667	pCVP2_BRI1_Citrine_bri1_T-bri1_T	GATA2	GATA2	GATA transcription factor 2	Down	Pericycle_Down
AT2G46400	Pericycle	28.200	50.7000	107.000	115.000	38.2000	37.100	0.16800	0.31300	⋯	37.6	2.36e-04	0.0497	0.007440	pCVP2_BRI1_Citrine_bri1_T-bri1_T	WRKY46	WRKY46	WRKY DNA-binding protein 46	Down	Pericycle_Down
AT2G48010	Pericycle	5.400	3.7000	8.260	7.570	2.4100	2.320	0.13300	0.08060	⋯	39.4	2.01e-04	0.0465	0.006650	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RKF3	NA	NA	Down	Pericycle_Down
AT4G01650	Pericycle	24.100	39.0000	11.400	9.640	41.6000	39.900	0.32200	0.39200	⋯	54.3	6.35e-05	0.0325	0.002970	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G01650	NA	NA	Up	Pericycle_Up
AT4G04223	Pericycle	1.720	0.1760	4.780	4.220	0.0000	0.000	0.02800	0.00474	⋯	51.7	1.43e-04	0.0409	0.005210	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G04223	NA	NA	Down	Pericycle_Down
AT4G11190	Pericycle	80.000	64.4000	197.000	204.000	91.7000	59.800	0.38500	0.27800	⋯	41.5	1.66e-04	0.0435	0.005820	pCVP2_BRI1_Citrine_bri1_T-bri1_T	DIR13	NA	NA	Down	Pericycle_Down
AT4G11211	Pericycle	250.000	269.0000	96.700	84.300	338.0000	314.000	0.82500	0.83900	⋯	87.8	1.04e-05	0.0156	0.000819	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G11211	NA	NA	Up	Pericycle_Up
AT4G12430	Pericycle	14.000	14.6000	5.090	4.620	12.3000	12.800	0.18200	0.18800	⋯	38.3	2.21e-04	0.0491	0.007120	pCVP2_BRI1_Citrine_bri1_T-bri1_T	TPPF	NA	NA	Up	Pericycle_Up
AT4G13860	Pericycle	8.100	10.6000	6.710	5.820	25.0000	18.600	0.15400	0.18500	⋯	50.9	8.01e-05	0.0357	0.003490	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G13860	NA	NA	Up	Pericycle_Up
AT4G15920	Pericycle	12.000	13.5000	2.730	1.200	12.4000	16.700	0.23800	0.23400	⋯	58.8	4.73e-05	0.0294	0.002400	pCVP2_BRI1_Citrine_bri1_T-bri1_T	SWEET17	NA	NA	Up	Pericycle_Up
AT4G16000	Pericycle	0.000	0.0588	3.910	3.670	0.0618	0.482	0.00000	0.00158	⋯	38.2	2.24e-04	0.0491	0.007180	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G16000	NA	NA	Down	Pericycle_Down
AT4G16990	Pericycle	12.000	5.8800	0.124	0.159	4.5100	3.090	0.22400	0.12500	⋯	95.0	7.67e-06	0.0142	0.000668	pCVP2_BRI1_Citrine_bri1_T-bri1_T	RLM3	NA	NA	Up	Pericycle_Up
AT4G22214	Pericycle	16.400	12.2000	55.200	32.400	17.1000	14.100	0.31500	0.20100	⋯	45.5	1.20e-04	0.0386	0.004620	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G22214	NA	NA	Down	Pericycle_Down
AT4G23450	Pericycle	11.800	15.3000	4.970	4.940	16.4000	17.800	0.18200	0.22300	⋯	63.3	3.59e-05	0.0270	0.001980	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AIRP1	NA	NA	Up	Pericycle_Up
AT4G23680	Pericycle	0.245	0.7050	5.900	3.430	0.3090	0.386	0.00699	0.00632	⋯	50.3	8.35e-05	0.0365	0.003590	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G23680	NA	NA	Down	Pericycle_Down
AT4G30660	Pericycle	8.840	10.2000	69.500	52.900	16.8000	23.400	0.22400	0.20400	⋯	41.1	1.73e-04	0.0435	0.005980	pCVP2_BRI1_Citrine_bri1_T-bri1_T	AT4G30660	NA	NA	Down	Pericycle_Down
AT4G36880	Pericycle	24.100	23.6000	63.600	51.900	26.6000	23.000	0.32200	0.27600	⋯	37.5	2.39e-04	0.0500	0.007510	pCVP2_BRI1_Citrine_bri1_T-bri1_T	CP1	NA	NA	Down	Pericycle_Down
AT4G39940	Pericycle	0.736	1.3500	20.100	16.000	5.5600	2.890	0.02100	0.02530	⋯	46.9	1.07e-04	0.0386	0.004290	pCVP2_BRI1_Citrine_bri1_T-bri1_T	APK2	NA	NA	Down	Pericycle_Down
AT4G39950	Pericycle	2.700	2.5300	57.000	49.300	9.8300	5.110	0.02800	0.04900	⋯	124.0	2.71e-06	0.0102	0.000338	pCVP2_BRI1_Citrine_bri1_T-bri1_T	CYP79B2	NA	NA	Down	Pericycle_Down

# add DE and up/dn to total list
sig_to_join <- sig_DE_fil %>%
mutate(clust_gene=paste(contrast, cluster_id, gene, sep="_")) %>%
select(clust_gene, up_dn_label, clust_up_dn)

all_bg <- mutate(all_bg, clust_gene=paste(contrast, cluster_id, gene, sep="_"))

all_bg <- left_join(all_bg, feature_names, by=c("gene"="AGI"))

all_bg$DE <- all_bg$clust_gene %in% sig_to_join$clust_gene

all_bg <- all_bg %>%
left_join(sig_to_join, by="clust_gene") %>%
arrange(all_bg, p_adj.loc)

write.csv(all_bg, file = "../output/CVP/all_genes_pCVP2_Citrine_celltype_EdgeR_q0.05_FC1.5_r_v_4_20240429.csv")

Plotting

rc.integrated$geno <- factor(rc.integrated$geno, 
                             levels=c("WT", "bri1_T", "pCVP2_BRI1_Citrine_bri1_T"))

options(repr.plot.width=16.5, repr.plot.height=6)
(Celltype_umap <- DimPlot(rc.integrated, 
                      reduction = "umap", 
                      group.by = "cell_type", 
                      cols = color, split.by = 'geno', 
                      ncol=3, 
                      pt.size = 0.5))

ggsave("../output/CVP/Cell_type_umap_square.pdf", width=16.5, height=6)

options(repr.plot.width = 18, repr.plot.height = 6)

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="BRI1-mCitrine", split.by = "geno", order=T, max.cutoff = "q90", pt.size = 0.5)

ggsave("../output/CVP/BRI1-mCitrine_expression.pdf", width=18.3, height=6)

Warning message in FeaturePlot(rc.integrated, features = "BRI1-mCitrine", split.by = "geno", :
“All cells have the same value (0) of BRI1-mCitrine.”

# expression of CVP2
options(repr.plot.width = 18, repr.plot.height = 6)

DefaultAssay(rc.integrated) <- "SCT"
# expression of the transgene
FeaturePlot(rc.integrated, features="AT1G05470", split.by = "geno", order=T, max.cutoff = "q90", pt.size = 0.5)

ggsave("../output/CVP/CVP2_AT1G05470_expression.pdf", width=18.3, height=6)